This method assigns a probability value to each vertex of the
network using the V1 information functional for vertex-labeled graphs. It is
based on the same principles as infoTheoreticGCM.

Usage

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Arguments

g

a graph as a graphNEL object. Each vertex must have an "atom" data
attribute specifying its atomic number or chemical symbol.

dist

the distance matrix of the graph. Will be automatically
calculated if not supplied.

coeff

specifies the weighting coefficients. Possible values are
"lin" (default), "quad", "exp", "const" or "cust". If it is set to
"cust" you have to specify your customized weighting schema with the
parameter custCoeff.

custCoeff

specifies the customized weighting scheme. To use it you
need to set coeff="cust".

coeffMatrix

overrides the "coeff" and "custCoeff" parameters to set
entirely user-defined coefficients for each pair of chemical symbol
(columns) and distance from the focussed vertex (rows). The columns have
to be named after the chemical symbols.

lambda

specifies the scaling constant for the distance
measures. The default value is 1000.